DocumentCode :
3534955
Title :
Smooth electric power scheduling in power distribution networks
Author :
Yingsong Huang ; Shiwen Mao ; Nelms, R.M.
Author_Institution :
Dept. of Electr. & Comput. Eng., Auburn Univ., Auburn, AL, USA
fYear :
2012
fDate :
3-7 Dec. 2012
Firstpage :
1469
Lastpage :
1473
Abstract :
The emergence of Smart Grid (SG) brings about many fundamental changes in electric power systems. In this paper, we study the problem of smooth electric power scheduling in power distribution networks. We introduce an electricity supply/demand model that takes into account the time-varying demands and their deadlines. We formulate a constrained nonlinear programming problem and incorporate the theory of majorization to develop algorithms that can compute smoothness optimal schedules for deferrable load dominant system. An effective heuristic algorithm is also presented by extending the majorization-based algorithm for the general scenario with mixed priority loads and deferrable loads. After obtaining the smooth power schedule, a distributed user benefit maximization load control scheme is used to allocate the scheduled power to individual users, while maximizing their level of satisfaction. The simulation results demonstrate the efficacy of the proposed algorithms on smooth electric power scheduling.
Keywords :
constraint handling; distribution networks; heuristic programming; load regulation; nonlinear programming; scheduling; smart power grids; SG; constrained nonlinear programming problem; deferrable load dominant system; distributed user benefit maximization load control scheme; electricity supply-demand model; heuristic algorithm; majorization-based algorithm; power allocation; power distribution network; smart grid; smooth electric power scheduling system; time-varying demand; Conferences; Decision support systems; Hafnium; Optimized production technology; Smart grids;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Globecom Workshops (GC Wkshps), 2012 IEEE
Conference_Location :
Anaheim, CA
Print_ISBN :
978-1-4673-4942-0
Electronic_ISBN :
978-1-4673-4940-6
Type :
conf
DOI :
10.1109/GLOCOMW.2012.6477802
Filename :
6477802
Link To Document :
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